Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:58
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=.5 EMIN=102 EMAX=95 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bodyweig
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    773.4569744  1.00000000  .500000000  102.000000  95.0000000
     1.3    617.1328571  1.05604530  1.31964135  105.265875  95.9499694
     2.2    578.7167491  .987291568  1.29017754  106.130054  94.9162265
     3.2    568.7901378  1.09738278  1.24339695  105.944784  94.7746267
     4.1    520.8024450  1.34428851  1.10119275  104.699012  93.8869652
     5.2    515.4277593  1.36348093  1.02726469  104.608828  93.9687856
     6.1    501.1910908  1.31908550  .710306881  104.348745  94.5334081
     7.1    501.1317924  1.30964805  .680208856  104.292075  94.6776080
     8.1    501.0638981  1.31120868  .698352248  104.323537  94.6261941
     9.1    501.0634385  1.30990155  .697066191  104.325291  94.6264923
    10.1    501.0632431  1.31031725  .697278176  104.323177  94.6269594

Run stopped after 10 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BODYWEIG

  Source                 DF  Sum of Squares  Mean Square

  Regression              4   707107.07768   176776.76942
  Residual               66      501.06324        7.59187
  Uncorrected Total      70   707608.14092

  (Corrected Total)      69     1639.41773

  R squared = 1 - Residual SS / Corrected SS =     .69437

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.310317246   .175596244   .959728032  1.660906460
  GSD         .697278176   .237712786   .222669285  1.171887067
  EMIN      104.32317713   .555167082 103.21475029 105.43160398
  EMAX      94.626959362   .824866471 92.980060314 96.273858409

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .1646    -.3296    -.5494
  GSD          .1646    1.0000     .3985    -.5416
  EMIN        -.3296     .3985    1.0000    -.1212
  EMAX        -.5494    -.5416    -.1212    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:58
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=1.14 EMIN=0.14 EMAX=0.03 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR thymus
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.07

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    .0395175805  1.00000000  1.14000000  .140000000  .030000000
     1.2    .0280068280  .995178942  1.14297001  .120081559  .033099820
     2.1    .0276655560  .994715692  1.14321073  .119576304  .036972713
     3.2    .0268028455  .919201744  1.15191604  .121162312  .037775768
     4.2    .0262704476  .800270180  1.14535125  .117958122  .038840433
     5.3    .0228724868  .336795684  .962437816  .123609928  .049690132
     6.3    .0222029992  .237109827  .921807571  .126621277  .047339980
     7.1    .0216468064  .149921741  .755211903  .128697165  .050939353
     8.1    .0215481942  .287102670  .695737134  .128445676  .049367164
     9.1    .0213779368  .237687898  .668781230  .127088594  .050451737
    10.1    .0213638516  .241099088  .646258379  .126339163  .050475132
    11.1    .0213634002  .244698175  .647226719  .126214090  .050360664
    12.1    .0213633825  .244487797  .646136319  .126221394  .050378109
    13.1    .0213633821  .244465292  .646315675  .126223724  .050377004
    14.1    .0213633821  .244470560  .646309594  .126223457  .050376961

Run stopped after 14 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable THYMUS

  Source                 DF  Sum of Squares  Mean Square

  Regression              4         .54192         .13548
  Residual               66         .02136   3.236876E-04
  Uncorrected Total      70         .56328

  (Corrected Total)      69         .09399

  R squared = 1 - Residual SS / Corrected SS =     .77270

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED          .244470560   .135226582  -.025518023   .514459142
  GSD         .646309594   .183965707   .279010209  1.013608979
  EMIN        .126223457   .004911621   .116417090   .136029824
  EMAX        .050376961   .003598161   .043193000   .057560922

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.1134    -.5047    -.3449
  GSD         -.1134    1.0000     .4906    -.3851
  EMIN        -.5047     .4906    1.0000    -.1028
  EMAX        -.3449    -.3851    -.1028    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:58
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=.65 EMIN=44 EMAX=1600 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR erod
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    19620041.24  1.00000000  .650000000  44.0000000  1600.00000
     1.3    8664649.942  .951370855  1.44994944  641.321491  1674.57100
     2.3    8471310.479  1.15709300  1.35278134  621.787622  1740.14927
     3.3    8359519.359  1.13315869  1.33259471  612.440012  1772.37941
     4.3    8356263.636  1.14341824  1.50676051  610.248276  1824.12585
     5.5    8202262.618  3.32907962  3.81249341  .000000000  3398.86187
     6.3    6156118.251  .827800265  2.11629545  21.2838297  2344.19132
     7.2    6145754.681  .952911908  2.23523600  20.4443949  2403.44346
     8.1    5914565.915  .152255794  2.16164744  14.9010769  1890.48296
     9.2    5765527.631  -.42687091  1.85871713  10.8915110  1514.00156
    10.1    5697799.569  -.85260604  1.51571967  7.30056141  1260.98764
    11.2    5130818.901  -1.1287949  .878194060  .000000000  1126.97344
    12.4    4945166.588  -1.0820585  .801311489  .000000000  1154.88648
    13.2    4859905.342  -1.0473640  .727958719  14.6390269  1153.12667
    14.1    4666425.655  -.83188503  .622695482  69.8035551  1194.71602
    15.1    4644974.519  -.81020658  .480400119  98.1294008  1170.79196
    16.1    4640011.400  -.83340928  .532257157  80.0128201  1175.93644
    17.1    4639243.045  -.82938145  .525359946  80.0927073  1175.31015
    18.1    4638811.062  -.83008633  .522452074  76.6678241  1174.04272
    19.1    4638692.727  -.83142032  .525448644  73.4208489  1174.02187
    20.1    4638672.093  -.83319240  .527620193  71.7662892  1173.93520
    21.1    4638671.431  -.83321989  .528134347  71.6650844  1174.04962
    22.1    4638671.413  -.83327164  .528113648  71.6734719  1174.03659

Run stopped after 22 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable EROD

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  38242420.5956  9560605.14889
  Residual               43  4638671.41273   107876.07937
  Uncorrected Total      47  42881092.0083

  (Corrected Total)      46  13310902.1055

  R squared = 1 - Residual SS / Corrected SS =     .65151

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.833271637   .180122414 -1.196523104  -.470020171
  GSD         .528113648   .249983791   .023973287  1.032254009
  EMIN      71.673471913 156.42294432 -243.7834597 387.13040351
  EMAX      1174.0365940 78.355224711 1016.0182236 1332.0549645




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.3376     .6661     .2382
  GSD         -.3376    1.0000    -.6436     .4137
  EMIN         .6661    -.6436    1.0000    -.1665
  EMAX         .2382     .4137    -.1665    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:58
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1.46 GSD=.0385 EMIN=0.310 EMAX=0.435 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR ffa
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.04

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    4.108393648  1.46000000  .038500000  .310000000  .435000000
     1.3    3.570290566  1.44963647  .038075064  .393860979  .531914279
     2.4    3.511858707  1.49160278  .068386744  .374611965  .574892858
     3.1    3.511472041  1.51797243  .072005460  .382361165  .571663295
     4.1    3.510138390  1.50792076  .058545142  .374328220  .568862352
     5.1    3.509609021  1.49982895  .068912557  .374000357  .565294102
     6.1    3.509265606  1.50442186  .071290212  .376384719  .567459124
     7.1    3.509263610  1.50426993  .070921566  .376221999  .567664163
     8.1    3.509263577  1.50430478  .070889034  .376219570  .567652855
     9.1    3.509263575  1.50431923  .070877063  .376219485  .567652091

Run stopped after 9 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable FFA

  Source                 DF  Sum of Squares  Mean Square

  Regression              4       14.39372        3.59843
  Residual               66        3.50926         .05317
  Uncorrected Total      70       17.90298

  (Corrected Total)      69        4.04924

  R squared = 1 - Residual SS / Corrected SS =     .13335

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.504319227  1.05669E+15 -2.10974E+15  2.10974E+15
  GSD         .070877063  2.75369E+15 -5.49792E+15  5.49792E+15
  EMIN        .376219485   .036011739   .304319727   .448119242
  EMAX        .567652091   .048080847   .471655583   .663648599

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    1.0000     .0000     .0000
  GSD         1.0000    1.0000     .0000     .0000
  EMIN         .0000     .0000    1.0000     .0000
  EMAX         .0000     .0000     .0000    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:58
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1.46 GSD=1.023 EMIN=1.58 EMAX=3.53 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bilirubi
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    55.04233980  1.46000000  1.02300000  1.58000000  3.53000000
     1.2    54.88486455  1.55911257  1.19820934  1.52947081  3.44193810
     2.3    54.47434649  1.66038904  1.39659198  1.60038931  3.55957171
     3.3    53.43122651  2.26180973  2.60597208  1.07055256  4.86747714
     4.1    53.15884290  2.60015024  2.39546188  1.22906942  4.93409064
     5.1    52.72989529  2.83567130  2.25479694  1.43648994  4.96231825
     6.1    52.62094148  2.74641039  2.35273135  1.39499517  5.00203555
     7.1    52.51486943  2.80575017  2.25317345  1.44049617  5.05349505
     8.1    52.35579517  3.00894914  1.95762372  1.54461341  5.31514430
     9.1    52.29437085  3.03209522  2.10319230  1.49281486  5.43461762
    10.2    52.22940926  3.21636163  2.24038906  1.47773455  5.72152022
    11.1    52.15642899  3.47700000  2.36796674  1.46758584  6.13770929
    12.1    52.15228132  3.47700000  2.34722802  1.47349298  6.15610430
    13.1    52.15052758  3.47700000  2.31552139  1.48312116  6.17412348
    14.1    52.15052671  3.47700000  2.31589301  1.48313913  6.17403563

Run stopped after 14 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BILIRUBI

  Source                 DF  Sum of Squares  Mean Square

  Regression              4      406.85947      101.71487
  Residual               66       52.15053         .79016
  Uncorrected Total      70      459.01000

  (Corrected Total)      69       90.08871

  R squared = 1 - Residual SS / Corrected SS =     .42112

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         3.477000000  6.497547457 -9.495772064 16.449772064
  GSD        2.315893010  3.533607351 -4.739181698  9.370967719
  EMIN       1.483139127   .433417754   .617792661  2.348485593
  EMAX       6.174035625 11.245061850 -16.27745475 28.625526004

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .9780    -.7221     .9987
  GSD          .9780    1.0000    -.8288     .9754
  EMIN        -.7221    -.8288    1.0000    -.7285
  EMAX         .9987     .9754    -.7285    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:58
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=.19 EMIN=192 EMAX=230 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR asat
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.08

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    8567532.949  1.00000000  .190000000  192.000000  230.000000
     1.4    5768052.836  .953023281  .187181397  240.272706  520.451250
     2.3    5557741.623  .978313415  .600631507  238.278425  530.661099
     3.2    5547035.261  .909928887  .896793742  232.807356  535.721638
     4.4    5204643.736  1.36557813  .866942561  198.478536  598.982813
     5.2    5179833.502  1.51286375  .975395077  216.048511  693.929008
     6.4    5102590.812  1.68801399  .907409586  225.064404  708.181091
     7.4    5065243.635  1.73504158  1.11110498  191.358520  716.486372
     8.3    5036559.968  1.82998592  1.06494798  196.876676  727.732924
     9.1    4983817.155  2.13845125  .856655291  222.588325  761.290138
    10.1    4982584.420  2.16604685  .905590053  221.376524  767.091147
    11.1    4981865.299  2.20080622  .942700482  221.488825  776.886397
    12.1    4980778.991  2.26075185  1.01850127  220.309685  799.055763
    13.1    4979852.074  2.32531819  1.07825593  219.291235  824.039816
    14.1    4979186.792  2.38014995  1.12335751  217.987153  847.892737
    15.1    4978991.055  2.41684847  1.14794143  217.285339  863.630802
    16.1    4978959.836  2.43921603  1.16589231  216.890776  872.971434
    17.1    4978956.052  2.45005817  1.17273320  216.813349  876.994178
    18.1    4978955.908  2.45206373  1.17478663  216.784332  877.821974
    19.1    4978955.900  2.45194101  1.17455673  216.790986  877.748103
    20.1    4978955.900  2.45193566  1.17455315  216.791419  877.743926

Run stopped after 20 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable ASAT

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  11537747.0998  2884436.77495
  Residual               66  4978955.90018    75438.72576
  Uncorrected Total      70  16516703.0000

  (Corrected Total)      69  7248533.84286

  R squared = 1 - Residual SS / Corrected SS =     .31311

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         2.451935658  1.443751501  -.430607219  5.334478534
  GSD        1.174553145  1.189083805 -1.199529270  3.548635561
  EMIN      216.79141901 57.418632917 102.15141954 331.43141847
  EMAX      877.74392584 557.64388126 -235.6280059 1991.1158576




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .8864    -.2465     .9781
  GSD          .8864    1.0000    -.5091     .9169
  EMIN        -.2465    -.5091    1.0000    -.3536
  EMAX         .9781     .9169    -.3536    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:58
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=.85 GSD=.304 EMIN=102 EMAX=80 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bodyweig
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.11

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    3905.286481  .850000000  .304000000  102.000000  80.0000000
     1.1    3011.119481  .927995791  1.53450121  109.201296  88.9301330
     2.2    2911.721135  .951149818  1.89979091  108.405657  87.2586819
     3.2    2683.950709  1.91674063  5.36047299  139.869684  35.0233226
     4.2    2667.475044  1.80063606  5.70211184  141.482647  33.3681206
     5.2    2502.998656  4.00000000  7.65577795  131.844540  20.7965835
     6.1    2197.314077  3.29527783  6.69494360  134.433779  26.7565292
     7.1    2186.687436  3.36528671  6.59576309  132.941275  27.9418831
     8.1    2168.821685  3.52391031  6.11989381  127.637694  32.9752563
     9.1    2162.026323  3.49781613  5.85333082  126.003399  35.2266213
    10.2    2104.879696  3.20618835  3.81646805  114.011633  52.2523552
    11.1    2091.985937  3.12642222  3.39895387  111.802857  55.6021618
    12.1    2050.493274  2.96261956  2.72112387  108.893791  60.3527704
    13.2    2001.854636  2.81380490  2.21154001  107.137356  63.4191635
    14.1    1944.891660  2.69305391  1.89391810  106.486037  64.7852715
    15.1    1867.062324  2.49631162  1.53632672  105.839603  66.8163542
    16.1    1788.229020  2.35455359  1.47328045  107.182279  65.3588513
    17.1    1747.984137  2.15965813  1.23477516  106.268118  68.1998780
    18.1    1675.586522  2.04777443  1.51393188  106.456163  68.9022597
    19.1    1658.266000  2.00922080  1.41038667  106.426461  69.7145924
    20.1    1462.137483  1.35217993  .439148405  104.779273  83.1356627
    21.2    1453.034542  1.34440031  .466765097  105.202721  82.5428526
    22.2    1452.730242  1.34179654  .464036817  105.207286  82.5759741
    23.1    1451.198081  1.32622832  .436608307  105.283046  82.9070762
    24.1    1451.164487  1.32888945  .439372122  105.295323  82.8836764
    25.1    1451.164161  1.32890904  .439006236  105.295824  82.8878078
    26.1    1451.164158  1.32892244  .438973499  105.295647  82.8877387

Run stopped after 26 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BODYWEIG

  Source                 DF  Sum of Squares  Mean Square

  Regression              4   604573.66336   151143.41584
  Residual               59     1451.16416       24.59600
  Uncorrected Total      63   606024.82752

  (Corrected Total)      62     7128.50903

  R squared = 1 - Residual SS / Corrected SS =     .79643




                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.328922444   .097476219  1.133872980  1.523971907
  GSD         .438973499   .135022434   .168794232   .709152765
  EMIN      105.29564717   .898952174 103.49684802 107.09444632
  EMAX      82.887738711  1.464918361 79.956443841 85.819033580

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .1543    -.2774    -.4955
  GSD          .1543    1.0000     .2910    -.4480
  EMIN        -.2774     .2910    1.0000    -.0679
  EMAX        -.4955    -.4480    -.0679    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=0.23 GSD=1.24 EMIN=0.058 EMAX=0.0033 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR thymus
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.04

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.1    .2839276299  .230000000  1.24000000  .058000000  .003300000
     1.1    .0447838246  .231281425  1.23976287  .129908565  .055887143
     2.1    .0291409337  .231396171  1.23920634  .153150179  .033973657
     3.1    .0291005545  .241102480  1.25195566  .153112671  .033646310
     4.1    .0290689411  .270019339  1.29125941  .154651976  .030478900
     5.1    .0288772117  .318901333  1.41142699  .154664006  .028418354
     6.1    .0288719719  .320636177  1.41564267  .155097584  .028485381
     7.1    .0288554755  .317751099  1.46136791  .156211883  .027495774
     8.1    .0288451168  .303182977  1.51588185  .157945195  .026419076
     9.1    .0288437803  .293508616  1.53333145  .158674120  .026156089
    10.1    .0288436314  .289020726  1.53699175  .158899927  .026149188
    11.1    .0288436189  .287889939  1.53650318  .158918023  .026185337
    12.1    .0288436177  .287721330  1.53590462  .158905789  .026205076
    13.1    .0288436176  .287752279  1.53578288  .158901384  .026207828

Run stopped after 13 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable THYMUS

  Source                 DF  Sum of Squares  Mean Square

  Regression              4         .58807         .14702
  Residual               59         .02884   4.888749E-04
  Uncorrected Total      63         .61691

  (Corrected Total)      62         .13676

  R squared = 1 - Residual SS / Corrected SS =     .78909

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED          .287752279   .319886502  -.352339133   .927843691
  GSD        1.535782883   .573073396   .389065666  2.682500101
  EMIN        .158901384   .019137352   .120607632   .197195136
  EMAX        .026207828   .014355312  -.002517085   .054932741

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.2654    -.6241    -.1952
  GSD         -.2654    1.0000     .8648    -.8330
  EMIN        -.6241     .8648    1.0000    -.5876
  EMAX        -.1952    -.8330    -.5876    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=-0.56 GSD=.34 EMIN=65 EMAX=1181 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR erod
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    2181515.508  -.56000000  .340000000  65.0000000  1181.00000
     1.5    2160525.112  -.56073870  .365474796  65.7816939  1181.16207
     2.5    2143148.112  -.57000930  .363185105  84.1818617  1198.10511
     3.4    2138756.774  -.54832823  .379390849  83.7824855  1215.36597
     4.3    2118223.526  -.57517966  .478820319  62.1844310  1225.35872
     5.1    2111987.165  -.55583438  .471497173  88.8564200  1217.61605
     6.3    2111908.524  -.55561081  .467733616  89.7710070  1216.85512
     7.2    2110826.214  -.55168169  .467770750  83.8034975  1215.93752
     8.1    2110799.786  -.55050761  .464509723  85.0061946  1215.78627
     9.1    2110799.592  -.55039676  .464638549  85.0091970  1215.90571
    10.1    2110799.588  -.55037619  .464663654  85.0102800  1215.92517

Run stopped after 10 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable EROD

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  27767205.7921  6941801.44803
  Residual               36  2110799.58822    58633.32189
  Uncorrected Total      40  29878005.3803

  (Corrected Total)      39  11020155.8833

  R squared = 1 - Residual SS / Corrected SS =     .80846

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.550376186   .110104297  -.773678051  -.327074320
  GSD         .464663654   .155346105   .149607150   .779720158
  EMIN      85.010279960 81.984094927 -81.26117114 251.28173106
  EMAX      1215.9251668 77.196183643 1059.3640499 1372.4862838

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.0088     .4575     .4339
  GSD         -.0088    1.0000    -.4711     .5025
  EMIN         .4575    -.4711    1.0000    -.1375
  EMAX         .4339     .5025    -.1375    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=1.02 GSD=.42 EMIN=0.33 EMAX=1.30 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR ffa
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    9.209737887  1.02000000  .420000000  .330000000  1.30000000
     1.3    4.205313262  1.08979884  .566211499  .511014294  .708583319
     2.5    3.470256797  1.50465086  .719031989  .407937070  .854669127
     3.3    3.138676856  1.72463196  .870560464  .483353727  1.00783727
     4.1    3.002408148  1.83670680  .806624042  .483473895  1.02869575
     5.2    2.860234754  1.95730816  .703065925  .486344315  1.05396395
     6.1    2.754329180  2.09764027  .518603206  .488303586  1.08634692
     7.1    2.747674240  2.07103321  .513514789  .480580899  1.08748881
     8.1    2.745772461  2.04976508  .500953739  .477796679  1.08985606
     9.1    2.745658523  2.04484135  .499381052  .478393963  1.08986017
    10.1    2.745648685  2.04449798  .497067759  .478791471  1.08970012
    11.1    2.745646339  2.04376180  .496918453  .478821703  1.08929225
    12.1    2.745643540  2.04216910  .495802258  .478816873  1.08840860
    13.1    2.745642336  2.04080579  .494468314  .478791552  1.08768652
    14.1    2.745642206  2.04054532  .494074353  .478778483  1.08756304
    15.1    2.745642201  2.04056046  .494047848  .478776283  1.08757556

Run stopped after 15 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable FFA

  Source                 DF  Sum of Squares  Mean Square

  Regression              4       26.20861        6.55215
  Residual               59        2.74564         .04654
  Uncorrected Total      63       28.95426

  (Corrected Total)      62        5.51318

  R squared = 1 - Residual SS / Corrected SS =     .50199

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         2.040560457   .223529317  1.593279327  2.487841587
  GSD         .494047848   .287270906  -.080779908  1.068875604
  EMIN        .478776283   .035501802   .407737341   .549815224
  EMAX       1.087575559   .123887705   .839676834  1.335474284

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .4798     .1297     .7532
  GSD          .4798    1.0000    -.2968     .6834
  EMIN         .1297    -.2968    1.0000    -.1242
  EMAX         .7532     .6834    -.1242    1.0000




Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=1.67 GSD=0.232 EMIN=1.89 EMAX=88 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bilirubi
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.08

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.4    99216.24909  1.67000000  .232000000  1.89000000  88.0000000
     1.2    349.3717976  1.72466429  1.73755207  1.83282484  11.0015703
     2.3    349.0496428  1.72539379  1.74566723  1.83206183  11.1860429
     3.6    210.1741210  2.07099866  1.39725128  1.46429573  13.2530157
     4.3    161.7871084  2.28671747  1.17993884  1.56740431  14.4688532
     5.5    143.4436612  2.38644338  1.18720411  1.07953294  16.9291172
     6.2    140.6670665  2.41095074  1.16066474  1.13300258  17.0351637
     7.1    134.7692643  2.55846675  1.01583581  1.55901702  17.9458920
     8.1    133.8778104  2.51996026  1.05839913  1.47798934  17.8131850
     9.1    133.7841241  2.52866223  1.05237980  1.49040367  17.9372567
    10.1    133.7307230  2.53440560  1.04812262  1.49807307  18.0534775
    11.1    133.6959829  2.53471077  1.04579858  1.50051946  18.0850805
    12.1    133.5531085  2.52904413  1.03584406  1.50774951  18.0974325
    13.1    133.2424949  2.50693615  1.01337930  1.52028200  17.9460231
    14.1    132.2506302  2.42353088  .945023491  1.55236714  17.1785610
    15.2    123.7883900  1.98722237  .618019923  1.69305062  12.8486151
    16.2    123.6543480  1.97527515  .608500695  1.69597115  12.7269399
    17.1    122.3829423  1.95413791  .569992575  1.66536701  12.3741795
    18.1    121.7619128  1.97574254  .552241724  1.64758544  12.3458095
    19.1    121.7603588  1.97663980  .551665708  1.65277356  12.3398540
    20.1    121.7602145  1.97709726  .552476789  1.65179679  12.3440546
    21.1    121.7602043  1.97704675  .552606723  1.65162520  12.3436040

Run stopped after 21 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BILIRUBI

  Source                 DF  Sum of Squares  Mean Square

  Regression              4     1909.75980      477.43995
  Residual               59      121.76020        2.06373
  Uncorrected Total      63     2031.52000

  (Corrected Total)      62      979.85714

  R squared = 1 - Residual SS / Corrected SS =     .87574

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.977046753   .095897543  1.785156212  2.168937294
  GSD         .552606723   .119207274   .314073519   .791139927
  EMIN       1.651625203   .244019299  1.163343713  2.139906693
  EMAX      12.343603960   .871870143 10.598995832 14.088212087




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .5209     .1188     .7834
  GSD          .5209    1.0000    -.3165     .7128
  EMIN         .1188    -.3165    1.0000    -.1384
  EMAX         .7834     .7128    -.1384    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=0.84 GSD=0.09 EMIN=242 EMAX=899 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR asat
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.07

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.4    6936338.300  .840000000  .090000000  242.000000  899.000000
     1.3    1773975.796  .908185371  1.16694047  236.778209  357.269514
     2.3    1457006.951  .247147371  .903964929  182.957914  396.434536
     3.6    952959.3103  1.17941106  1.24031650  137.508482  505.516370
     4.7    942017.2450  1.18502344  1.33733816  149.351212  519.336670
     5.1    872273.8425  1.36660199  1.24371595  156.793812  539.920298
     6.1    756697.4331  1.47574473  1.07943623  156.943635  571.886021
     7.1    710202.4127  1.55705990  .971170410  161.979634  583.064360
     8.1    651165.8705  1.58338081  .859990151  163.576713  603.857984
     9.3    637455.3161  1.61473862  .800694060  166.748279  605.422643
    10.2    624079.5228  1.66957928  .949743255  166.411427  668.221151
    11.1    596891.9080  1.67384984  .661673423  170.506785  654.000165
    12.1    594386.2699  1.74014121  .678046782  176.024018  661.618640
    13.1    594262.5911  1.74900120  .708997093  174.863811  665.933253
    14.1    594211.2696  1.75206708  .704304379  174.785323  666.778641
    15.1    594207.2914  1.75438272  .705274265  174.665233  667.630348
    16.1    594207.1732  1.75486540  .705893563  174.642924  667.832724
    17.1    594207.1704  1.75492500  .706000315  174.642296  667.860578

Run stopped after 17 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable ASAT

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  7868778.82964  1967194.70741
  Residual               59   594207.17036    10071.30797
  Uncorrected Total      63  8462986.00000

  (Corrected Total)      62  2495174.88889

  R squared = 1 - Residual SS / Corrected SS =     .76186

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.754925003   .182369552  1.390004373  2.119845632
  GSD         .706000315   .222126706   .261525802  1.150474827
  EMIN      174.64229631 18.927335330 136.76878580 212.51580683
  EMAX      667.86057800 64.031324952 539.73419272 795.98696329




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .5662     .1027     .8173
  GSD          .5662    1.0000    -.3788     .7547
  EMIN         .1027    -.3788    1.0000    -.1815
  EMAX         .8173     .7547    -.1815    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=.85 GSD=.304 EMIN=102 EMAX=80 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bodyweig
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.03

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    770.2252961  .850000000  .304000000  102.000000  80.0000000
     1.2    681.9605938  .843725682  .413406495  102.086117  79.9625789
     2.1    574.2840972  .794014800  .499915302  104.210343  78.7050154
     3.3    541.7308076  .752064608  .519101188  104.098122  78.1089840
     4.2    539.8413407  .706748716  .508393789  104.224676  78.8837493
     5.1    520.9150667  .726339480  .629681205  104.243390  77.9462293
     6.1    520.4402316  .740129432  .626320640  104.171922  77.8731174
     7.1    520.4318702  .742263177  .626439007  104.164978  77.8437091
     8.1    520.4316963  .742442534  .626717583  104.165879  77.8384984
     9.1    520.4316812  .742482718  .626840020  104.166392  77.8370414

Run stopped after 9 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BODYWEIG

  Source                 DF  Sum of Squares  Mean Square

  Regression              4   496889.27595   124222.31899
  Residual               50      520.43168       10.40863
  Uncorrected Total      54   497409.70764

  (Corrected Total)      53     5904.26105

  R squared = 1 - Residual SS / Corrected SS =     .91185

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED          .742482718   .089890830   .561931671   .923033764
  GSD         .626840020   .114441207   .396978092   .856701949
  EMIN      104.16639217   .716632089 102.72699425 105.60579008
  EMAX      77.837041424  1.717754179 74.386830616 81.287252233

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .4251    -.1970    -.7380
  GSD          .4251    1.0000     .4094    -.7060
  EMIN        -.1970     .4094    1.0000    -.1760
  EMAX        -.7380    -.7060    -.1760    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=0.23 GSD=1.24 EMIN=0.058 EMAX=0.0033 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR thymus
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.1    .2246101982  .230000000  1.24000000  .058000000  .003300000
     1.1    .0226177065  .231179778  1.23949833  .137606000  .038206581
     2.1    .0145253552  .230604918  1.23859779  .151715883  .014705572
     3.2    .0143038611  .193792475  1.22732835  .151746338  .015618512
     4.2    .0132315919  -.02079117  1.15096711  .156097628  .025829139
     5.1    .0131219179  -.05850841  1.12645434  .158471873  .025263874
     6.1    .0126671819  -.20503565  .988287277  .157294571  .033849436
     7.1    .0123108820  -.17601637  .895631977  .152832339  .035467783
     8.1    .0118754937  -.09863337  .691470512  .144352486  .038372351
     9.1    .0117896241  -.07295508  .703515689  .145594792  .036414687
    10.1    .0117762728  -.09364077  .664848532  .146226101  .038060135
    11.1    .0117655820  -.07834123  .679632904  .145795512  .037557905
    12.1    .0117654569  -.08083514  .680953186  .145890444  .037552545
    13.1    .0117654409  -.08041553  .679630722  .145848702  .037567124
    14.1    .0117654395  -.08039502  .679908911  .145855926  .037565558
    15.1    .0117654395  -.08040869  .679905626  .145855959  .037565269

Run stopped after 15 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable THYMUS

  Source                 DF  Sum of Squares  Mean Square

  Regression              4         .54211         .13553
  Residual               50         .01177   2.353088E-04
  Uncorrected Total      54         .55388

  (Corrected Total)      53         .11597

  R squared = 1 - Residual SS / Corrected SS =     .89855

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.080408695   .093319472  -.267846370   .107028981
  GSD         .679905626   .128232609   .422342851   .937468402
  EMIN        .145855959   .004987364   .135838543   .155873376
  EMAX        .037565269   .004603089   .028319693   .046810845

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.0478    -.4971    -.4394
  GSD         -.0478    1.0000     .5663    -.5330
  EMIN        -.4971     .5663    1.0000    -.1812
  EMAX        -.4394    -.5330    -.1812    1.0000




Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=-0.56 GSD=.34 EMIN=65 EMAX=1181 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR erod
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    9684350.927  -.56000000  .340000000  65.0000000  1181.00000
     1.3    8622570.017  -.59372779  1.50314026  344.749207  1471.30265
     2.2    7296436.067  -.81801518  1.26499822  289.764901  1749.80870
     3.2    6002772.661  -.44058063  1.16668394  267.065245  2000.28138
     4.4    5451732.235  -.46448939  .906453245  206.980920  2064.70700
     5.2    5433686.243  -.33090283  .975170968  200.787632  2153.92107
     6.4    4948752.972  -.81418064  .741393775  142.650688  1670.69509
     7.3    4928728.196  -.84367174  .717306909  141.321143  1637.22736
     8.3    4836980.404  -.86297446  .659867998  .000000000  1592.52796
     9.4    4819328.330  -.87602439  .585934431  42.8148477  1547.25798
    10.6    4781878.467  -.89738490  .631946180  42.0011764  1591.15984
    11.2    4778544.661  -.88636383  .619080206  60.9021636  1586.24579
    12.1    4776717.738  -.86171252  .585579021  97.0364859  1576.41987
    13.1    4776480.747  -.86634039  .599230614  86.0418604  1580.60668
    14.1    4776465.222  -.86590965  .596513407  87.5881997  1580.01143
    15.1    4776465.009  -.86568109  .596426405  87.8272499  1579.99141
    16.1    4776465.003  -.86571121  .596446682  87.7879099  1579.99959

Run stopped after 16 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable EROD

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  39212724.0378  9803181.00944
  Residual               32  4776465.00300   149264.53134
  Uncorrected Total      36  43989189.0408

  (Corrected Total)      35  15775785.0613

  R squared = 1 - Residual SS / Corrected SS =     .69723

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.865711208   .199754336 -1.272597475  -.458824941
  GSD         .596446682   .311669396  -.038403103  1.231296467
  EMIN      87.787909890 238.21097925 -397.4319765 573.00779631
  EMAX      1579.9995927 183.35739137 1206.5128085 1953.4863770




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.1948     .5927     .3287
  GSD         -.1948    1.0000    -.7538     .6790
  EMIN         .5927    -.7538    1.0000    -.3754
  EMAX         .3287     .6790    -.3754    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1.02 GSD=.42 EMIN=0.33 EMAX=1.30 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR ffa
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.1    5.825375429  1.02000000  .420000000  .330000000  1.30000000
     1.2    4.564457237  1.04705519  .439513972  .517669207  1.27315703
     2.3    4.364729701  1.14961371  .432539630  .523607586  1.19154001
     3.1    4.261643728  1.22368328  .406021777  .530432850  1.23095781
     4.2    4.173287344  1.26961275  .310610068  .542153120  1.23895529
     5.1    4.152851684  1.35399741  .202637069  .544147098  1.29486207
     6.1    4.142798333  1.35133697  .271046854  .543000782  1.30279492
     7.1    4.139125876  1.32693064  .271154100  .545362735  1.28686540
     8.1    4.138101282  1.32338637  .253763219  .545274090  1.28328856
     9.1    4.138034228  1.32276967  .257162357  .544106459  1.28526603
    10.1    4.138033229  1.32269642  .256833449  .544238827  1.28507374
    11.1    4.138033227  1.32268450  .256836091  .544241925  1.28507248

Run stopped after 11 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable FFA

  Source                 DF  Sum of Squares  Mean Square

  Regression              4       29.87225        7.46806
  Residual               50        4.13803         .08276
  Uncorrected Total      54       34.01029

  (Corrected Total)      53        7.95473

  R squared = 1 - Residual SS / Corrected SS =     .47980

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.322684505   .136530238  1.048455451  1.596913558
  GSD         .256836091   .151382294  -.047224196   .560896377
  EMIN        .544241925   .048086838   .447656668   .640827181
  EMAX       1.285072482   .124727032  1.034550864  1.535594099

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.0474     .2546     .5277
  GSD         -.0474    1.0000    -.2574     .3449
  EMIN         .2546    -.2574    1.0000    -.0221
  EMAX         .5277     .3449    -.0221    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1.67 GSD=0.232 EMIN=1.89 EMAX=88 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bilirubi
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.11

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.4    21959.71261  1.67000000  .232000000  1.89000000  88.0000000
     1.3    2980.975775  1.83232489  4.70271680  1.72021912  27.4110956
     2.3    2086.371749  1.78683522  4.64701428  1.69980013  16.2471144
     3.2    1407.358551  3.47700000  3.21689511  .000000000  31.9536988
     4.1    1377.958865  3.24947868  3.36315543  .000000000  30.9618346
     5.1    1162.677413  3.23375896  2.98850831  .000000000  37.1272214
     6.2    939.6440400  3.19447757  2.47455552  .000000000  43.9730350
     7.1    766.6534042  3.02890207  2.09681006  .000000000  48.8930387
     8.2    572.6287430  2.74491388  1.70065433  .000000000  53.9202674
     9.2    505.2693557  2.66735475  1.50568009  .280257672  55.8847451
    10.4    484.3720559  2.61918163  1.46555905  .272739868  56.4925105
    11.2    418.5355825  2.52038986  1.25241253  .670249084  58.4610861
    12.1    373.4664626  2.35600599  .934992074  1.37772624  61.1236859
    13.1    369.9316218  2.38365808  .997324504  1.45642467  60.5029074
    14.1    369.4837050  2.37961133  .974054124  1.57396919  60.6087719
    15.1    369.4550953  2.37085522  .969261488  1.55788655  60.6248540
    16.1    369.4110287  2.37443638  .973018690  1.55079211  60.5682781
    17.1    369.3493542  2.37195296  .972237183  1.55809824  60.2535409
    18.2    367.9100365  2.27077182  .936495193  1.55614227  54.4276446
    19.2    367.6334058  2.24994375  .926018557  1.57358700  53.3368086
    20.1    366.5339958  2.12773020  .869042121  1.55675924  47.2837370
    21.1    365.7757536  2.04242632  .827594614  1.68801478  43.1551627
    22.2    364.5849098  1.70435241  .555338053  2.08572567  30.9551116
    23.1    359.1574180  1.56401634  .457292282  2.19170298  25.6516004
    24.3    357.8636770  1.51340092  .426202651  2.19360319  23.9118417
    25.2    345.9325260  1.52446608  .515778934  1.75457512  25.8576757
    26.1    344.9547469  1.50593508  .503273989  1.83724664  25.3912466
    27.1    343.7528593  1.46455323  .467589348  1.90467156  24.2168450
    28.1    342.4423085  1.43287170  .432769313  1.93667315  23.4500581
    29.1    341.2915254  1.42425306  .407888897  1.91556198  23.4068071
    30.1    341.0922737  1.41947410  .396559242  1.88987539  23.1379349
    31.1    341.0796827  1.42740902  .403314763  1.87769971  23.3384160
    32.1    341.0708829  1.42447937  .400913121  1.88296071  23.2657905
    33.1    341.0708565  1.42430563  .400694326  1.88315167  23.2605130
    34.1    341.0708565  1.42431253  .400701935  1.88314586  23.2606894

Run stopped after 34 major iterations.
Optimal solution found.





Nonlinear Regression Summary Statistics     Dependent Variable BILIRUBI

  Source                 DF  Sum of Squares  Mean Square

  Regression              4     4218.03914     1054.50979
  Residual               50      341.07086        6.82142
  Uncorrected Total      54     4559.11000

  (Corrected Total)      53     2769.13204

  R squared = 1 - Residual SS / Corrected SS =     .87683

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.424312525   .090103334  1.243334652  1.605290398
  GSD         .400701935   .108942016   .181885455   .619518414
  EMIN       1.883145860   .450001941   .979290360  2.787001359
  EMAX      23.260689379  2.497844581 18.243620885 28.277757872

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .6931     .0203     .8715
  GSD          .6931    1.0000    -.2809     .8108
  EMIN         .0203    -.2809    1.0000    -.1568
  EMAX         .8715     .8108    -.1568    1.0000

Constrained Nonlinear Regression

Notes
Output Created		02-FEB-2002 13:47:59
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=0.84 GSD=0.09 EMIN=242 EMAX=899 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR asat
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.07

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.4    2489233.579  .840000000  .090000000  242.000000  899.000000
     1.2    1868002.804  .855459219  .334167596  240.816098  899.635646
     2.1    1354273.239  2.15060391  1.41613238  141.630966  2761.61418
     3.5    1021907.711  2.30532183  1.38091799  129.782316  2770.65733
     4.4    991325.2417  2.33471077  1.35714367  159.280391  2764.83870
     5.2    879695.6613  1.51417969  .662626305  216.671070  1684.52080
     6.1    868286.3011  1.40741747  .636206071  218.870053  1521.26523
     7.1    848056.0132  1.55883556  .715711936  210.247323  1717.40993
     8.1    835318.6966  1.65308455  .761761171  202.370096  1795.41397
     9.1    832117.7498  1.54460900  .709180003  202.137218  1646.73559
    10.1    831769.1343  1.53267293  .697743149  203.013949  1634.56234
    11.1    831693.5717  1.51780751  .686138885  203.031498  1614.44812
    12.1    831683.5679  1.52177976  .687448098  202.660999  1620.50759
    13.1    831680.3767  1.52066951  .686745207  202.776024  1618.25221
    14.1    831680.3684  1.52066101  .686761151  202.766830  1618.21760

Run stopped after 14 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable ASAT

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  17770090.6316  4442522.65789
  Residual               50   831680.36844    16633.60737
  Uncorrected Total      54  18601771.0000

  (Corrected Total)      53  7943102.83333

  R squared = 1 - Residual SS / Corrected SS =     .89530

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.520661014   .276955849   .964378819  2.076943208
  GSD         .686761151   .211593817   .261762462  1.111759840
  EMIN      202.76682961 25.414466407 151.72037153 253.81328769
  EMAX      1618.2176030 387.51496694 839.87088507 2396.5643209

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .9213    -.2259     .9855
  GSD          .9213    1.0000    -.4067     .9361
  EMIN        -.2259    -.4067    1.0000    -.2957
  EMAX         .9855     .9361    -.2957    1.0000

